Metadata and Radio

Metadata and Radio

Metadata and Radio
update // enrich // amend

Aim

What is radio metadata?

Organisations – name, logo, address / contact

Radio stations – name, strapline, logo, address / contact, audio streams,

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genres, languages

Shows – name, DJ, text description, genres, logo, related information (webpage, twitter etc)

Episodes – name, text description, tracklist, audio stream (and availability?), broadcast date(s), image, related information (webpage, twitter etc)

Instantaneous – what’s happening now?
text description, webpage, what track, what DJ, feeds / activity, what’s on next

Different types of metadata
Music metadata – what track is playing now?
artist, label, title, genre, version, release date, publisher, full duration, broadcast time/duration

User metadata
who? where? likes, dislikes, listening history, friends … and what they like, listen to etc

——————————————————————————————————————

How can metadata affect user experience?
Do my friends send it to me?
Does it surprise me with new stuff?
Once I’m listening, is there more I’d like?

Radio Discovery metadata – example

  • Creating ‘content dna’ for stations and programmes
  • This could be ‘tracks played’ or ‘topics discussed’ etc
  • It needs to be a common, simple, open standard
  • It needs to be generated automatically and stored forever
  • This could power discovery APIs for radio
  • If you ‘like this, try this’ for radio
  • Chapterised browsing – straight in to content

Radio Discovery metadata – solutions

Utility

  • Does it ‘just work’?
  • Is it there when I need it?
  • Is it an effort to learn how to use it?
  • Does it ‘automagically’ seem to know me?

Radio Utility metadata – example

  • A way of radio devices sensing location, taste, mood etc…
  • ….without requiring a heavy login process
  • This could be used to tailor recommendations
  • And to auto cache suitable content into a tailored channel

Radio Utility metadata – solutions

  • Prototype radio integration with existing social apps
  • Investigate emerging ‘radioTAG’ technologies
  • Consider low barrier login processes
  • Agree common descriptors for user location data etc
  • Understand data protection implications of user data driven radio
  • Quantify commercial upside for location/taste targeted ads

Engagement

  • Does it make me feel cool to use it?
  • Does it draw me in for more?
  • Does it react to my needs?
  • Is it a joy to be with?

Radio Engagement metadata – example

  • Visually rich browsing modes for audio material
  • Tactile, responsive, beautifully crafted interfaces

Engagement metadata – solutions

What are the challenges / what have

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we discovered

  • Delivery of programme / song / clip metadata is not always efficient since there is currently no single common standard.
  • Without the extra metadata, it’s difficult to discover radio content or to produce detailed analytics.
  • The production processes are inconsistent, there is a lot of duplication and it is prone to human error because of undeveloped tools/processes.
  • Producers don’t understand the role of metadata and how that can translate to an audience and/or income.

How do we get there / solutions?

Develop content management solutions and tools that automate the creation and clean up of rich metadata particularly for smaller radio stations and producers.

Adopt a structured but expandable set of standards to cover our metadata needs.

  • There are a large number of standards to consider when representing radio data. In choosing Atom, we are avoiding creating more standards and using the best available feed format.
  • What is Atom?
  • Atom is a feed format similar to RSS2 but with significant advantages. As a feed format it contains a series of entries, in reverse date order, but any XML data can be embedded within it.
  • Why do we want to use Atom?
  • Because it has a defined publishing protocol (Atompub), Atom offers a defined structure and as such provides a better foundation for deploying a CMS.

Real time interrogation of music fingerprinting technology and longer term research in to speech recognition technologies.

  • music intelligence and metadata services like The Echo Nest, Gracenote, Music Brainz, Discogs, Decibel etc will be an integral part of how radio is re-invented; listened, discovered and shared.

Music fingerprinting technologies are deployed in:

Outro
A core objective of Radio Connected, was to continue building on best practise for metadata standards used by radio service providers. It was

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decided that the most effective method of dissemination was via a Wiki which would open up the discussion to the widest community and encourage further innovation.

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